Accurate Modeling of Indoor Environments Using a LiDAR for Efficient mmWave Network Planning and Understanding mmWave Propagation Channel Characteristics
Project runs from 02/05/2020 to 03/31/2020
There is ample literature on channel models and network planning for sub-6 GHz frequencies. However, since the channel propagation characteristics at millimeter-wave (mmWave) bands are significantly different from that of the sub-6 GHz bands, for reliable results, designated solutions are needed for mmWave systems. The major challenge with the mmWave frequencies is the high loss rates in terms of both free-space path loss and penetration losses. Therefore, while planning the mmWave network, it is utmost important to model the environment accurately, i.e., dimensions of the rooms, furniture, objects, material types, etc. In this project, we will use a LiDAR sensor for 3D mapping of indoor environments and transfer the created maps to Wireless InSite software to find the optimal base station (BS) locations that maximize the coverage rate. We will also generate binary occupancy maps from the LiDAR maps and use them along with the analytical channel models in machine learning algorithms to automate the mmWave BS placement. Indoor maps created with the LiDAR sensor will also provide the opportunity for a fair comparison between the channel measurements from the ray-tracing simulations and the measurements from the real-life experiments conducted with our NI-based channel sounder.